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Could race differences in demand account for the pattern? Banks are still harder to get to in low-poverty, college-educated, minority homeowner neighbourhoods than high-poverty, low-education, white renter neighbourhoods a–c, Adjusted probability that an AFI is faster to get to by foot (a), public transport (b) and car (c), based on model behind Fig. 1 (Supplementary Table 1a–c). All variables are set at the grand means except as follows: the bars on the left show the probability that an AFI is closer for neighbourhoods with 50% low income with unemployment at the 75th percentile (14% unemployed) of the total distribution, proportion college educated at the 25th percentile (11%) and proportion homeowner at the 25th percentile (25%); the bars on the right, for neighbourhoods with 10% low income with unemployment at the 25th percentile (5% unemployed), proportion college educated at the 75th percentile (47%) and proportion homeowner at the 75th percentile (71%). Error bars represent 95% confidence intervals. Number of observations: 21,852 for travel by car, 21,313 by public transport, 21,800 by foot. Source data
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Research has made clear that neighbourhood conditions affect racial inequality. We examine how living in minority neighbourhoods affects ease of access to conventional banks versus alternative financial institutions (AFIs) such as check cashers and payday lenders, which some have called predatory. Based on more than 6 million queries, we compute th...
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... Residents of neighborhoods with higher education and socioeconomic status have higher levels of financial knowledge (Angrisani et al., 2021;La Chance, 2014). Other work also shows that neighborhood characteristics can explain why alternative financial institutions are more prevalent in neighborhoods with racial and ethnic minorities (Small et al., 2021). Physical location and geographic proximity of financial institutions play a key role in the decision, especially by small businesses, to own a bank account. ...
We review journal publications from 2007 to 2023 that specifically study or consider racial/ethnic and gender differences in financial knowledge. Of the 32 papers we review, 12 focus on racial/ethnic differences, 7 focus on gender differences, and 13 consider racial/ethnic and gender differences. From these studies, we estimate that, on average White adults score 17 percentage points higher than Black adults on objective financial knowledge, 14 percentage points higher than Hispanic adults, and 2 percentage points lower than Asian adults. We also estimate that, on average, men score 13 percentage points higher than women on objective financial knowledge. We also provide average racial/ethnic and gender differences in subjective financial, knowledge, and these differences across groups seem much smaller. We provide an overview of possible determinants for these racial/ethnic and gender gaps in financial knowledge. We discuss how stakeholders should leverage research on financial knowledge and directions for future research with the purpose to address racial/ethnic and gender gaps in financial knowledge in the United States.
... Growing research has examined how spatial distance from institutions, such as banks and nonprofits, shapes access to resources (e.g., Allard 2009;Thomas 2010;Faber 2019;Small et al. 2021). But we know far less about other barriers people may encounter in the immediate vicinity and interior spaces of institutions (Gose 2023), and scholars have yet to fully conceptualize how spatial barriers operate alongside rules and norms to regulate marginalized people in their encounters with the state. ...
... Public health scholars and legal scholars, for instance, have sought to catalogue and quantify institutional "deserts" of various kinds (e.g., "food deserts" and "legal deserts") (see Thomas 2010;Pruitt et al. 2019). Recent work in public policy has also considered how spatial distance from banks (Faber 2019;Small et al. 2021) and nonprofit service organizations (Allard 2009) may reproduce race and class inequality. Meanwhile, urban sociologists have shown how neighborhood residence enables and constrains access to jobs and educational opportunities (Allard and Danziger 2002) as well as access to "third places," such as coffee shops and barbershops (Oldenburg and Brissett 1982;Small and McDermott 2006). ...
This article theorizes how space shapes access to state institutions, and with what consequences. Drawing on 125 interviews and over 400 hours of ethnographic observations concerning two criminal courthouses within the same county, we identify four spatial features that differentially shape access while working alongside institutional rules and norms: functional distance, neighborhood social life, exterior built forms, and interior built forms. When they constrain access, these features constitute spatial burdens, which contribute to distinct institutional and collateral costs concentrated among marginalized groups. We theorize how these costs likely reproduce systemic patterns of inequality by extending people’s burdensome interactions with the state institution they seek to access and compelling them to interact with other state institutions that further the state’s power over their lives. The theory of spatial burdens has implications for the study of poverty governance and institutional inequality.
... Finally, future work is needed on racial inequality in addition to income disparities. UI and other state benefits may be distributed in racially unequal patterns, and racial discrimination and inequalities in access to credit may result in high exposure to high-cost credit among Black and Hispanic populations [40][41][42] . In particular, economic conditions improved fastest over the course of the pandemic for the highest-income groups, resulting in what some have characterized as a k-shaped recovery, such that the lowest-income groups, which disproportionately include marginalized racial and ethnic populations, continued to face unemployment and underemployment far longer than more privileged workers in positions more easily transitioned to remote work 43,44 . ...
US consumers may turn to the private market for credit when income and government benefits fall short. The most vulnerable consumers have access only to the highest-cost loans. Prior research on trade-offs of credit with government welfare support cannot distinguish between distinct forms of unsecured credit due to data limitations. Here we provide insight on credit–welfare state trade-offs vis-à-vis unemployment insurance generosity by leveraging a large sample of credit data that allow us to separate credit cards, personal loans and alternative financial services loans and to analyse heterogeneity in credit use by household income. We find that more generous state unemployment insurance benefits were associated with a lower probability of high-cost credit use during the first seven quarters of the coronavirus disease 2019 (COVID-19) pandemic. This inverse association was concentrated among consumers living in low-income households. Our results support theories that public benefits are inversely associated with the use of costly credit.
... By living in the same area and sharing the same norms, resources, and routines, residents of the same neighborhood are likely to share a neighborhood identity that can also evolve into formal, i.e., organizational, and informal, i.e., friendship, local networks (Sampson and Groves, 1989). In contrast to friendships, this joint neighborhood identity is not necessarily based on interaction but can evolve through local and semi-conscious norm-diffusion (Mayer and Jencks, 1989) and joined local institutions (Small et al., 2021). High similarity among neighbors can foster the emergence of such norms and institutions either because of a higher probability of successful collective organization or because of more pronounced social control in homogeneous groups (Campbell et al., 2009;Hipp, 2007;Hipp et al., 2012;Sampson et al., 2002). ...
Studying the relationship between neighborhoods and individual-level outcomes such as crime, labor market success, or intergenerational mobility has a long history in the social sciences. As local processes such as gentrification or residential mobility constantly change neighborhoods’ composition and spatial expansion, time-constant one-size-fits-all neighborhood measures fail to capture important local dynamics. This paper presents a flexible and data-driven approach for efficiently estimating overlapping and arbitrarily shaped neighborhoods with time-dynamic boundaries. Constructed in a two-stage clustering design, the first stage identifies homogeneous groups within a city (using an automated K-Means algorithm), while the second stage clusters homogeneous groups by spatial proximity (using the HDBSCAN algorithm). In an analysis of 86 million person-year observations from 76 German cities, the paper shows that a larger spatial expansion of neighborhoods with a high socioeconomic status negatively correlates with city crime cases, while higher neighborhood fragmentation and heterogeneity correlate positively with crime rates. The findings stress the importance of flexible neighborhood estimation techniques and the necessity to view neighborhoods as non-constant entities. By modeling contexts as such agentic players, the two-staged algorithm depicts a novel and transparent tool to consider the spatial embeddedness of individuals, firms, or regions in sociological research.
... Surprisingly, the coefficient is most negative for institutions in census tracts with the largest proportions of Black residents. Prior work reports that minority neighborhoods have less access to banks than White neighborhoods 42 . In addition to lower supply, the fact that proportions of Black people are lowest even in census tracts in the 25th percentile for proportions of Black residents suggests less demand for these services. ...
While residential segregation is a persistent attribute of metropolitan areas, recent studies find segregation levels fluctuate throughout the day, reaching their lowest levels during daytime hours. This paper shows hourly variations in Black-White segregation from Monday through Sunday for the top 49 most populated metropolitan areas with Global Positioning System (GPS) data collected from mobile phones from October 2018. I find that segregation levels are higher on average over weekends compared to that of weekdays. I use models to identify the characteristics of neighborhoods with higher levels of segregation on weekends, which include all demographic variables and nearly a third of 35 sectors of businesses and organizations, such as retail, personal care, and religious organizations. I also find more than a third of the sectors are associated with higher levels of segregation during business hours on weekdays, including academic institutions, health care, manufacturing, and financial institutions. Findings from this paper display the significance in the distinction between weekdays and weekends with where people spend their time and how this relates to racial segregation. Specifically, Black people, on average, stay in their home census tracts and visit non-White neighborhoods for organizational resources more so than White people. Significant patterns of associations between racial segregation and the majority of businesses demonstrate the salience of race for more industries than previously understood.
... We extracted the association estimates for the White population percentage from the models that included the variables percent Black and percent White. Other studies have used a similar approach 58,59 . We used the following hierarchical model formulation: ...
Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors—counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.
... Recent intra-city research highlighted the importance of integrating road networks for effective facility accessibility assessment 13 . These measurements, coupled with spatial distributions of subpopulations within cities, have spurred cross-disciplinary research measuring inequality in accessibility to specific facilities like healthcare services [14][15][16] , sanitation facilities 17,18 , banks 19 , parks [20][21][22] , and schools 23 , with a special focus on vulnerable groups' constrained accessibility. However, the pivotal role of transit networks in sustainable urban development has been overlooked in evaluating facility accessibility. ...
Urban transit networks are crucial for developing sustainable cities, yet uneven transit infrastructure distribution often leads to unequal access to urban resources. Prior studies utilize simple spatial metrics to measure accessibility, overlooking systemic inequality within transit networks and its real-world implications. Utilizing door-to-door travel information within a complex transit network, we probe racial inequality in transit-oriented accessibility to various urban resources and assess its impact on mobility behaviours. Our analysis reveals minority neighbourhoods endure consistently reduced transit-oriented accessibility to urban areas, job opportunities, and essential facilities by 15.2%, 37.3%, and 37.0%, respectively, compared to White-majority neighbourhoods. The uneven accessibility to urban areas exacerbates residential segregation by 32.1% relative to the equitable scenario. Regarding behavioural consequences, low accessibility subjects minority neighborhoods to constrained activity spaces, elevated unemployment risks, and extended travel distances to essential facilities. To inform potential mitigation policies, we conduct simulation experiments and discover that solely enhancing transit-oriented developments in minority-concentrated public housing districts can reduce current racial inequality by 8.8%. Our findings emphasize the imperative of prioritizing equity and inclusiveness in designing future sustainable transit systems.
... Neighborhood contexts are spatially unequal, with interactions between structural conditions and business strategies contributing to the unequal distribution of neighborhood amenities across communities (Logan & Molotch, 1987;Massey & Denton, 1993). This includes financial services; for example, high-cost payday lenders disproportionately target Black and low-income communities when opening storefronts (Prager, 2014;Small et al., 2021). The local composition of financial services has important implications for families' use of services and financial well-being (Célerier & Matray, 2019;Friedline & Kepple, 2017;Melzer, 2018). ...
... For example, banks tend to open branches in higher-income areas while AFS open in low-income areas where there might be higher demand for small dollar loans (Burkey & Simkins, 2004;Damar, 2008). At the same time, organizational branching is stratified along racial lines in ways that do not necessarily align with profit maximization; for example, it is more common for an AFS storefront to be closer than bank branch in low-poverty Black neighborhoods compared to high-poverty White neighborhoods (Small et al., 2021; see also Faber, 2019). ...
... After identifying the six distinct financial service investment trajectories, I descriptively analyze tract characteristics for each trajectory group. Point-in-time studies across multiple disciplines have found that banks are disproportionately located in wealthier and whiter communities, while AFS services tend to cluster in lower-income communities and communities with higher shares of Black and Latino residents (Prager, 2014;Small et al., 2021). I consider whether similar findings hold when evaluating trajectories over time. ...
Drawing on techniques more commonly used to study changes within families over time, this paper highlights how holistic life course methods can help scholars conceptualize the dynamic nature of local built environments and measure impacts for families and communities. I use a novel dataset on the historical availability of banks, credit unions, and alternative financial services (AFS) between 2003 and 2015 to classify neighborhoods by their financial service trajectories using sequence and cluster analyses. I identify six distinct trajectories of financial service availability over the 13-year period; neighborhoods in these trajectories differ in terms of their socioeconomic and demographic characteristics. Descriptive multivariate analyses confirm that trajectories are linked to community outcomes at the end of the period; tracts exposed to AFS at some point over the 13 years are associated with higher predicted end-of-period poverty rates compared to both tracts that are only exposed to banks and credit unions and tracts that are chronic financial service deserts. Extensions of this approach to other aspects of the built environment are discussed.
... Another factor that may drive or inhibit segregated mobility patterns is the varying prevalence of certain institutions and establishments. Small et al. (2021) found that the distribution of alternative financial institutions (such as check cashers and payday lenders) varies considerably compared with that of conventional banks. Specifically, alternative financial institutions tend to be abundant in minority neighborhoods, such that the travel time to alternative financial institutions is less than that of a bank more often in highpoverty minority neighborhoods than in low-poverty White neighborhoods. ...
Nascent research documents that U.S. racial segregation is not merely a residential phenomenon but is present in everyday mobility patterns. Better understanding the causes of mobility-based segregation requires disentangling the spatial macrosegregation, which constitutes an obvious confounding factor. In this work, the author analyzes big data on everyday visits between 270 million neighborhood dyads to estimate the effect of neighborhood racial composition on mobility patterns, net of driving, walking, and public transportation travel time. Matching on these travel times, the author finds that residents of Black and Hispanic neighborhoods visit White neighborhoods only slightly less than they visit other Black and Hispanic neighborhoods. Distinctly, residents of White neighborhoods are far less likely to visit non-White neighborhoods than other White neighborhoods, even net of travel time. The author finds that this travel time–adjusted visit homophily among White neighborhoods is greater in commuting zones where White neighborhoods are situated closer to non-White neighborhoods.
... Similarly, future research could use geospatial data to further explore inequality in access to key infrastructure and facilities such as financial institutions (Small et al. 2021), transit (Jiao and Cai 2020), schools, hospitals, government agencies, and city centers to estimate the economic and societal costs these inequalities create. Spatial inequality also attenuates the consequences of climate change in poorer neighborhoods as they tend to feature less vegetation, fewer trees, and a greater degree of soil surface sealing making them more vulnerable to heavy rain falls, extreme heat, and poor air quality (Miller and Hess 2017;Saverino et al. 2021). ...
Going back to Huff’s seminal gravity model in the 1960’s, geospatial data has a long history in marketing research. Its applications in research and practice range from location-based mobile targeting of individual consumers to store competition analyzes and city marketing. Over the past decades, geospatial data has become more readily available than ever and has grown considerably in breadth (i.e., countries and regions covered) and depth (i.e., granularity and diversity of information covered). Nonetheless, international marketing research has not yet fully embraced the opportunities that geospatial data brings to the field. To address this shortcoming, this paper shows how geospatial data may propel international marketing research in various domains and develops future research questions for the field. In addition, it introduces OpenStreetMap (OSM) as a rich and open-source geospatial data source to the discipline. The use of geospatial data in general and OSM more specifically is illustrated through a concrete application in which the authors analyze city center composition in nine countries across three continents. In doing so, they reproducibly describe the extraction of geospatial data, constructions of metrics and operationalizations, as well as visualizations.
